Evidence map›Paper›PMID 27892682›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2016

Can Serum ICAM 1 distinguish pancreatic cancer from chronic pancreatitis?

amal mohamed, Yasmine Saad, Doaa Saleh, Rehab Elawady, Rasha Eletreby, Ahmad S Kharalla, Eman Badr

Abstract read
In one paragraph

Article in Asian Pacific journal of cancer prevention : APJCP, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
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  3. Article
  4. Review
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  8. ImmunoPET/NIRF/Cerenkov multimodality imaging of ICAM-1 in pancreatic ductal adenocarcinoma.European journal of nuclear medicine and molecular imaging · 2021
    Article
  9. Review
  10. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

amal mohamedDepartment of Medical Biochemistry, National Hepatology and Tropical Medicine Research Institute, Cairo, Egypt. Email: r_m_tawfik@yahoo.com
Yasmine Saad
Doaa Saleh
Rehab Elawady
Rasha Eletreby
Ahmad S Kharalla
Eman Badr

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aim: Pancreatic cancer is the fourth leading cause of cancer-related death worldwide, with an overall 5-year survival of <5% mainly due to presence of advanced disease at time of diagnosis. Therefore development of valid biomarkers to diagnose pancreatic cancer in early stages is an urgent need. This study concerned the sensitivity and specificity of serum ICAM 1 versus CA 19-9 in differentiation between pancreatic cancer and healthy subjects and acohort of patients with chronic pancreatitis with a focus on assessing validity in diagnosis of early stages of pancreatic cancer. Methods: A cohort of 50 patients with histologically diagnosed pancreatic tumors, 27 patients with chronic pancreatitis, and 35 healthy controls were enrolled. Serum samples for measurement of CA19-9 and I-CAM 1 were obtained from all groups and analyzed for significance regarding diagnosis and disease stage. Results: At a cut off value of (878.5 u/ml) I-CAM 1 had 82% and 82.26% sensitivity and specificity for differentiation between cancer and non-cancer cases, with higher sensitivity and specificity than CA19-9 at different cut offs (CA19-9 sensitivity and specificity ranged from 64-80% and 56.4 – 61.2% respectively). The AUC was 0.851 for I-CAM and 0.754 for CA19-9. Neither of the markers demonstrated significance for distinguishing between early and late cancer stages. Conclusion: ICAM 1 is a useful marker in differentiation between malignant and benign pancreatic conditions, and superior to CA19-9 in this regard. However, neither of the markers can be recommended for use in differentiation between early and late stage pancreatic cancers.

Indexed as

CA19-9chronic pancreatitisI-CAMPancreatic cancer

Identifiers

PMID27892682
PMCPMC5454615

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.